A Joint Sensing, Communication, and Task Offloading Framework for Vehicular Metaverse
Recently, metaverse-empowered wireless systems have gained significant interest in the
research community because of the appealing features of self-sustainability and proactive …
research community because of the appealing features of self-sustainability and proactive …
A Joint Sensing, Learning, and Communication Framework for Vehicular Metaverse
M Alghfeli - 2024 - dclibrary.mbzuai.ac.ae
Recently, metaverse-empowered wireless systems have gained significant interest in the
research community because of the appealing features of proactive learning and self …
research community because of the appealing features of proactive learning and self …
Task offloading and resource allocation in vehicular networks: A Lyapunov-based deep reinforcement learning approach
AS Kumar, L Zhao, X Fernando - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) has gained popularity due to its ability to enhance
vehicular networks. VEC servers located at Roadside Units (RSUs) allow low-power …
vehicular networks. VEC servers located at Roadside Units (RSUs) allow low-power …
Latency-aware placement of vehicular metaverses using virtual network functions
Recent unprecedented trend towards novel vehicular network applications (eg, lane change
assistance, collision avoidance, accident reporting, and infotainment) led to research …
assistance, collision avoidance, accident reporting, and infotainment) led to research …
Computation offloading and resource allocation in MEC-enabled integrated aerial-terrestrial vehicular networks: A reinforcement learning approach
As important services of the future sixth-generation (6G) wireless networks, vehicular
communication and mobile edge computing (MEC) have received considerable interest in …
communication and mobile edge computing (MEC) have received considerable interest in …
Resource allocation in MEC-enabled vehicular networks: A deep reinforcement learning approach
Mobile edge computing (MEC) is a promising technique to liberate mobile vehicles from
increasingly intensive computation workloads and improve the quality of computation …
increasingly intensive computation workloads and improve the quality of computation …
Eco-vehicular edge networks for connected transportation: A distributed multi-agent reinforcement learning approach
This paper introduces an energy-efficient, software-defined vehicular edge network for the
growing intelligent connected transportation system. A joint user-centric virtual cell formation …
growing intelligent connected transportation system. A joint user-centric virtual cell formation …
Edge intelligence empowered vehicular metaverse: Key design aspects and future directions
Emerging intelligent transportation system applications witnessed significantly different
requirements and performance metrics (eg, latency, reliability, and quality of experience). To …
requirements and performance metrics (eg, latency, reliability, and quality of experience). To …
Toward intelligent vehicular networks: A machine learning framework
As wireless networks evolve toward high mobility and providing better support for connected
vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular …
vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular …
Diffusion-based Reinforcement Learning for Dynamic UAV-assisted Vehicle Twins Migration in Vehicular Metaverses
Air-ground integrated networks can relieve communication pressure on ground
transportation networks and provide 6G-enabled vehicular Metaverses services offloading in …
transportation networks and provide 6G-enabled vehicular Metaverses services offloading in …